02/24/2015

With the new equation for Effective Demand, I want to go back and pull out the Aggregate Supply - Effective Demand model from past posts. To see those posts, you can click on the link at the right under Categories.

Here is what the model looks like from 4thQ-2012 to 4thQ-2014.

The interesting thing is that the effective demand limit curves kept pointing to the same place since 2012... see circle around $16300 billions in real GDP (2009 dollars). Those ED limit lines show more consistency than before.

The last two lines of 2014 (purple and black) starting moving away from the circle destination. 3rdQ-2014 is the purple line just starting to rise away from the others. 4thQ-2014 is the black line which jumped to a higher level. So, just as real GDP was hitting the $16300 level in the second half of 2014, which would have constrained the economy, effective demand found a way to jump to a higher level. The main causes were easing of monetary policy, lower long-term rates and falling headline inflation.

Is effective demand shifting to a new level? I will be watching the new data as it comes in...

02/20/2015

I just want to make public the spreadsheet that I use for calculating Effective Demand. I cleaned it up a bit.

You will be able to see the equations in the individual cells. The flow of how the information is processed may be hard to follow. You would have to "trace the precedents and dependents" of each cell to see how the information flows.

The second sheet is the one that I use for regressions. I have to copy over the ED-FF numbers from the "NGDP adj inflation target" sheet each time I do an iteration of a regression.

The third sheet was the preliminary calculations before I incorporated the equation for NGDP targeting. I include it just for the record.

02/19/2015

In my analysis of effective demand, I can see the state of the economy before the Federal Reserve responds with their Fed rate.

Here is the graph of the final difference between the effective demand limit and the utilization of labor and capital (TFUR) after monetary policy has been taken into consideration.

We see that the difference falls to between 0% and -2% before a recession happens. We also see that currently, the difference is above 0% implying that a recession is not imminent.

Now here is a graph of the difference between the effective demand limit and the utilization of labor and capital before monetary policy is taken into consideration.

In the 1970's, the economy was far below -2%, but easy monetary policy boosted it back up as seen in the first graph. Since 1980, the economy always reached around -2% before going into a recession. In 2014, the economy reached once again that -2% level implying that the economy was sensitive to recessionary forces.

Since 2014, effective demand is rising again due to falling headline inflation and falling long-term treasury rates. You can see that in the first graph, the plot is pushed above the 0% level by super aggressive monetary policy. However, if it were not for these effects of easy monetary policy and falling oil prices, we might have seen more of a correction in the stock market.

The economy is hitting a level which in the past meant that the economy had reached its maximum level of employing labor and capital before a recession happened. However, super aggressive monetary policy is keeping the economy expanding. How much can monetary policy keep the economy expanding beyond this point? We will see...

If monetary policy does start to tighten, and oil prices start to rise again... then I would expect to see recessionary forces awaken. But the economy may have another way to postpone a recession. Something to watch.

02/16/2015

Effective Demand seeks to identify the end of a business expansion in the business cycle. This post will present a method to determine the coefficients in the effective demand equation to determine the effective demand limit upon the business cycle.

Defining the Top of the Business Cycle

In order to determine an equation to describe the top of a business cycle, we first need to identify the tops of a business cycle. I measure the business cycle by multiplying capacity utilization by (1 - unemployment rate). I call this composite measure T in the graph below. This measure gives a view into how capital and labor is being utilized throughout the business cycle.

The graph shows that the utilization of capital and labor rises and falls throughout the business cycle. I have connected the tops of the cycle with a yellow line. This yellow line will represent how the top potential of the business cycle has changed through time. The tops of business cycles are connected with a straight line. Whether the yellow line should dip below or hover above a straight line is not explored at this stage of the research. So the tops are connected with a straight line.

The effective demand equation will be determined by regressing variables against the yellow line. The idea is to develop an equation that will describe the behavior between T and effective demand at the top of the past business cycles since 1967.

Independent Variables to determine Effective Demand

In order to determine an equation for Effective Demand, we need to have independent variables to put into our regression. The dependent variable in the regression will be the yellow line connecting the tops of the "T" business cycle above.

Here is a list of the independent variables to be regressed. (All data is quarterly begining in 1967 because capacity utilization data began in 1967 according to data source, FRED.)

Labor Share Index of National Income. (data) The labor share index as given by the US Bureau of Labor Statistics. Labor share will represent the final consumption power of society apart from the income of profits, which are left over after paying out labor income.

Headline Inflation. (data) The CPI of all items. Inflation represents how prices cut into demand. A higher inflation will lower potential demand.

Looseness or Tightness of the Federal Funds rate. A loose Fed rate will raise potential demand. This variable will be determined using the NGDP effective demand rule for monetary policy. This variable depends upon the coefficients used for the other independent variables, so there will be a series of iterations of the regression which change the other coefficients. The iterations will arrive at stable coefficients for all independent variables. (shown later) (Note: Core inflation is factored into the NGDP effective demand rule. See this post for its comparison to Headline inflation.)

Looseness or Tightness of Long-term Interest rates. (data) The year-over-year change of the difference between the 10-year Treasury (constant maturity) minus the Fed rate. If the 10-year falls in relation to the Fed rate, then demand potential is raised.

Population Growth rate. (data) The faster the population grows, the more demand potential would grow too.

Yearly Change of Real GDP. (data from US Bureau of Economic Analysis, table 1.1.6) As real GDP grows, demand potential should fall. More products and services, all other variables equal, should lower demand potential resulting in less capital and labor utilized in businesses.

Government Expenditures as a percentage of Real GDP. (data from US Bureau of Economic Analysis, table 1.1.6) The more the government spends, the more demand potential there should be.

Net Exports as a percentage of Real GDP. (data from US Bureau of Economic Analysis, table 1.1.6) The more net exports are in relation to total production, the more demand potential there should be.

Private Investment as a percentage of Real GDP. (data from US Bureau of Economic Analysis, table 1.1.6) The more private investment there is in relation to total production, the more demand potential there should be.

Iterations of Regressions to Determine the Coefficients

These independent variables are put into a regression. Estimated coefficients are used to start the iterations of the regression due to the variable (EDrule - Fed rate) needing a start. The starting estimated coefficients do not affect the ultimate result.

No residual factor is used in order to constrict the result to the variables chosen.

The initial estimation of this equation against the top demand potential (yellow line above) looks like this.

The first iteration of the regression gives these results.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.724

0.050

14.574

0.000

0.626

0.822

cpiall

-1.056

0.069

-15.302

0.000

-1.192

-0.920

ed-ff

86.338

5.589

15.449

0.000

75.312

97.364

10-ff

-0.656

0.088

-7.456

0.000

-0.829

-0.482

G

32.153

11.453

2.808

0.006

9.558

54.749

r growth

-0.483

0.082

-5.869

0.000

-0.645

-0.320

I

25.174

20.518

1.227

0.221

-15.307

65.654

nx

34.331

19.060

1.801

0.073

-3.274

71.935

pop

-2.080

0.969

-2.146

0.033

-3.992

-0.168

According to the P-values, Investment (I) and Net Exports (NX) are not significant enough to describe the effective demand limit by having values over 5%. The highest T stats point to labor share, headline inflation, monetary effects and real GDP growth as the most significant variables.

After 6 iterations, the results look like this.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.69316

0.04859

14.26542

1.41E-31

0.597294

0.789026

cpiall

-1.13543

0.071273

-15.9306

1.79E-36

-1.27605

-0.99481

ed-ff

87.10909

5.554219

15.68341

9.45E-36

76.15095

98.06723

10-ff

-0.44419

0.083452

-5.32273

2.95E-07

-0.60884

-0.27955

G

43.9263

11.15365

3.93829

0.000116

21.92082

65.93178

r growth

-0.19435

0.079358

-2.44901

0.015262

-0.35092

-0.03778

I

29.42429

20.27896

1.450976

0.148489

-10.5849

69.43348

nx

47.67543

18.85586

2.528415

0.012298

10.47395

84.87692

pop

-2.97525

0.96935

-3.06932

0.00247

-4.88772

-1.06278

Now the only independent variable with a P-value too high for significance is Investment (I). Investment will be dropped from the regression. Then the regression iterations will be run over again.

Here is how the coefficients change over the 6 iterations giving two examples. All coefficients trend toward a stable value.

Second Run of Regression Iterations without Investment

After 6 iterations of the regression without investment, the results look like this.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.759053

0.018787

40.40267

1.01E-93

0.721988

0.796118

cpiall

-1.13232

0.071133

-15.9182

1.68E-36

-1.27265

-0.99198

ed-ff

88.26595

5.387935

16.38215

7.43E-38

77.63626

98.89565

10-ff

-0.46773

0.081525

-5.73728

3.87E-08

-0.62857

-0.30689

G

29.49403

5.457594

5.404218

1.99E-07

18.72691

40.26115

r growth

-0.12814

0.06538

-1.95997

0.051502

-0.25713

0.000844

nx

27.20015

12.30226

2.210989

0.028262

2.929399

51.4709

pop

-2.77093

0.955917

-2.89871

0.0042

-4.65683

-0.88503

The variable pushing the limits of significance for a P-value is real GDP growth. The regression iterations will be run again without real GDP growth.

Third Run of Regression Iterations without Real GDP Growth

After 6 iterations of the regression without real GDP growth, the results look like this.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.758384

0.018787

40.3675

5.85E-94

0.721321

0.795447

cpiall

-1.09859

0.068206

-16.1069

4.08E-37

-1.23315

-0.96404

ed-ff

87.68955

5.366844

16.33913

8.52E-38

77.10184

98.27726

10-ff

-0.39175

0.071212

-5.50122

1.24E-07

-0.53224

-0.25127

G

28.0139

5.426011

5.162891

6.22E-07

17.30947

38.71834

nx

26.34758

12.29211

2.143454

0.033376

2.097702

50.59745

pop

-2.85751

0.95646

-2.98759

0.003191

-4.74442

-0.97061

The variable with less significance for a P-value when compared to the other variables is Net Exports/rGDP. The regression iterations will be run again without Net Exports/rGDP.

Third Run of Regression Iterations without Net Exports/rGDP

After 6 iterations of the regression without Net Exports/rGDP, the results look like this.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.729557

0.012576

58.01381

1.7E-121

0.704748

0.754365

cpiall

-1.02953

0.059659

-17.2568

1.54E-40

-1.14722

-0.91184

ed-ff

86.61256

5.30586

16.32394

8.11E-38

76.14552

97.07959

10-ff

-0.37225

0.070746

-5.26183

3.88E-07

-0.51182

-0.23269

G

33.8623

4.607057

7.350093

5.99E-12

24.77381

42.95078

pop

-2.03106

0.866964

-2.34273

0.020195

-3.74135

-0.32077

The variable with less significance for a P-value when compared to the other variables is population growth. The regression iterations will be run again without population growth.

Fourth Run of Regression Iterations without Population Growth

After 6 iterations of the regression without population growth, the results look like this.

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

0

#N/A

#N/A

#N/A

#N/A

#N/A

lsi

0.713623

0.009986

71.45959

3.2E-138

0.693923

0.733323

cpiall

-1.01453

0.059451

-17.0648

4.71E-40

-1.1318

-0.89725

ed-ff

85.47596

5.282628

16.18057

1.85E-37

75.05511

95.8968

10-ff

-0.37906

0.070897

-5.3467

2.58E-07

-0.51892

-0.23921

G

32.05953

4.617768

6.942646

6.07E-11

22.95023

41.16883

The P-values all show high significance.

Evaluating the Final Equation for Effective Demand

Using the coefficients in the last regression run, the effective demand equation looks like this.

In this above graph, the effective demand limit (orange line) is currently rising. Towards the end of 2014, there was concern about the economy. The stock market had a correction. Then the price of oil started to fall and the 10-year long-term rates started to fall. The combination of those two made effective demand start to rise. The economy and the stock markets have been rising upon this resuscitation of effective demand.

The resulting Effective Demand rule rate is now compared to the Fed rate. When the Fed rate (red line) is below the blue line, the Fed rate is looser than the effective demand limit would prescribe.

Concluding thoughts

The resulting equation could be used as a guide to assess when the end of the business cycle might occur. Still, the economic environment must be evaluated because the effective demand limit may just slow down utilization of capital and labor instead of lead it into recession. The research into effective demand continues.

The effective demand blog here has spent almost 2 years using labor share as the only variable for effective demand. The P-value of the above regression results show that labor share has the highest significance for the effective demand limit. So the principles developed over the last two years are not lost. They have paved the way to a better understanding of the current equation.

Real GDP growth may still have a significant influence. If I add real GDP growth with a coefficient of 0.40, the plot matches up better to the peaks, for example in the late 1960's, 1980, 1984 and 2005. This addition also shows how close T and effective demand came together before the stock market correction in the 3rd quarter of 2014. I want to put the graph here for reference.

The peaks of the business cycle have been smoothed out more in relation to effective demand... especially the peak in 1984, which did not lead to a recession, but still led to an economic contraction. They all fall within the -1% to -2% range, with the exception of the peak in 1973, which surpassed the range, but led to a quick and deep recession. (The red dots are the starts of recessions.)

How does the growth in real output affect effective demand?

When output increases, there are more options for the consumer to purchase goods & services. Demand becomes weaker for any one firm in the aggregate. With more production, prices would have to drop in order to keep effective demand steady. For example, I did a simple test of the equation by increasing yearly real output growth from 0% to 2%. In order for effective demand to stay the same, headline inflation would have to drop by 2%, from a 3% inflation target to 1%. Core inflation would also have to drop just 1% from 3% to 2% keeping the central bank base nominal rate unchanged.

01/16/2015

In the equation for NGDP targeting for a policy rule, there are two components of the Fed rate, real growth of output and the effects of inflation.

I thought it would be helpful to post a graph that separates out those two components side by side. The data for the graph comes from my equations for determining the short-term real rate and the inflation response in the Fed rate. (link) My equations determine the short-term real rate and the inflation response, and then add them together to prescribe a Fed rate.

First here is my equation plotted against the actual Fed rate. The blue line represents my equation to determine the Fed rate.

Now I will separate out the two components of my equation for the Fed rate.

The blue line here shows the short-term real rate which reflects real output growth. You can see that it normally plateaued between 2% and 4% since the 1960's. Normally real output growth was in the 3% range. But since the crisis, we see that real output growth is still below 2%. The economy is sick, unproductive and demand constrained.

The orange line represents the response to inflation so that nominal GDP would return to its price level target. The general pattern shows that the need to control inflation has been going lower. Now we have the reverse where there is a need to liberate inflation.

The complication now is that real output growth is suffering at the same time that inflation pressures are weak.

For example, if Lr = 1.8% and a Ct of 2.5% is desired, then Nt will be established at 4.3%. Nt is meant to be constant over time. If actual NGDP diverges from Nt, then inflation will need to over-compensate to bring NGDP back to its target over time. When actual core inflation falls below Ct, then, NGDP will fall below target. Then eventually core inflation will have to rise above Ct in order for the NGDP target to return back to its target. In this way, the NGDP target is maintained. For example, if NGDP drops below 4.3%, then NGDP will have to go above 4.3% in the future to compensate the drop. David Beckworth has estimated that maybe 5% would be a good NGDP target, but he recognizes that it may be above or below 5%.

The Federal Reserve is actually able to set the long-run average core inflation target, Ct. This then will determine Nt.

I use core inflation for the long-run inflation target instead of the headline inflation, even though nominal GDP is based on headline inflation. Monetary policy should not be based on headline inflation.

The problem with this equation is that Ct is a constant. The equation makes inflation return to Ct, instead of leading it beyond Ct when necessary to compensate for previous divergences from Ct. This equation does not work for NGDP targeting.

(a is a weighting coefficient for how strongly the Fed rate should move inflation back to target (Ct).)

So, an equation for adjusting the inflation target, Ct, is needed. Replace Ct with an adjustable core inflation target, Ca.

Policy rate rule with adjustable inflation target, PRa.

PRa = Sr + Ca + (1+a)*(C - Ca)

Now, I need to define Ca for how to adjust the core inflation target (Ct) for NGDP targeting.

Ca = Ct + Ct - average of past core inflation(Cv)

Ca = Ct + Ct - Cv

Ct = Ca - Ct + Cv

Cv depends on how far back core inflation is averaged. Cv is a "NGDP targeting" adjustment of Ct for when average core inflation (Cv) has been different from Ct. If Cv = Ct, then Ca = Ct. When Cv has been below Ct, then Ca will rise to a higher inflation target, which allow NGDP to rise above Nt so that NGDP returns to its Nt target averaging over time.

The idea of Ca is this... If Cv has been averaging 2.0% (below the desired Ct of 2.5% for NGDP targeting), then Ca will rise to 3.0% until you are able to bring NGDP back to a long-term average of 4.3%.

Now, substitute in for Ca in the PRa equation. Ca = Ct + Ct - Cv

PRa = Sr + Ca + (1+a)*(C - Ca)

PRa = Sr + Ct + Ct - Cv + (1+a)*(C - (Ct + Ct - Cv))

Simplify equation...

PRa = Sr - 2aCt + aCv + (1+a)C

This is the final equation that I use as a policy rate rule to move NGDP toward its long-term NGDP targeting goal. (a = weighting coefficient)

The equation embodies the equation for the NGDP target (Nt). Substitute in for Ct = Nt - Lr.

PRa = Sr - 2a(Nt - Lr) + aCv + (1+a)C

PRa = Sr + 2a(Lr - Nt) + aCv + (1+a)C

So now to determine the short-term real rate (Sr), I use my effective demand monetary rule. You could use another method.

OK... everything is in place to test the equation. Now I compare the PRa equation to the actual Fed rate assuming a core inflation average (Cv) based on the previous 2.5 years. Core inflation target (Ct) of 2.5% is kept constant through time series for simplicity. Natural real rate (Lr) has changed over time from 3% in the 1970's to 1.8% currently. And finally a =0.5.

The lines do not match perfectly for many reasons, but that is not the present goal. The goal is to make a policy rate rule where the Fed rate steers inflation to a nominal GDP target, not just an inflation target.

The PRa equation implies that the Fed rate was very loose in the 1970's. Since the 1970's, the PRa equation has trended with the Fed rate.

In order to get the lines to match up perfectly, the parameters would have to coincide with each specific data point in time. What was the inflation target? What is the best time period for averaging core inflation? What was the estimated short-term real rate in each period? What method was used to determine the Fed rate at each data point.

I will change the parameters so that the lines match better. I make a = 0.3, Cv based on previous 3 years, Ct = 3% and the same Lr.

The PRa equation for NGDP targeting is saying that the Fed rate should be around 2.5% to 3% currently based on the parameters given above. The parameters can be changed.

01/14/2015

A nominal GDP target makes sense. If inflation runs below target for a while, it makes sense for inflation to run over target in the future in order to achieve the desired long run growth to inflation.

So how might a policy rule to determine the Fed rate be modified for a NGDP target?

So if core inflation runs over target, the policy rule rate rises to move inflation back down to target. As well, if core inflation runs below target, the policy rule rate drops to move inflation back up to target.

However, in nominal GDP targeting, the idea is to move inflation beyond the desired long run inflation target in order to compensate for the time being off target. So for example, if core inflation runs below target, the inflation target in the policy rule would be raised to guide inflation to a higher level above the target.

Thus the inflation target in the policy rule would have to be adjusted to allow core inflation to average to its long run target. The adjusted inflation target could look like this...

Let's put this equation to a graph. I plot core inflation (blue) over time going through periods over a 2% target, followed by periods under the target.

The orange line gives the adjusted inflation target through time averaging all the previous core inflation from time 0. So as core inflation is averaged over longer and longer time periods, the adjusted inflation target for NGDP targeting stabilizes near 2%. The grey line is the adjusted inflation target if core inflation is averaged after it ran below target. That line too will stabilize near 2% through time.

Whether the adjusted inflation target is measured from time 0 or time 4, it will stabilize near the constant inflation target currently used in policy rules. So is there really a need for adjusting the inflation target?

Let's apply this equation to core inflation data since 1967. In the following graph, the line represents the inflation target that you would use now depending on how far back you averaged core inflation. For example, if you averaged core inflation back to 1987, you would need an adjusted inflation target of 1.3% in your current policy rule, instead of the constant 2.0% being used.

If you averaged core inflation back to the end of 2008, you would use an adjusted inflation target of 2.3%, which is already close to the 2.0% inflation target being used. If you averaged back to the 1960's, you would use an adjusted target of -0.2%. So there is a big difference depending on how far back you average core inflation. Your adjusted inflation target for the policy rule may be above or below your desired long-run target.

The graph above assumes a long-run inflation target of 2.0% for NGDP targeting. What if you desired a LR inflation target of 3.0%?

Even though you have raised your inflation target by 1%, the adjusted inflation target for the policy rule rises by 2.0%. The 1987 target rose from 1.3% to 3.3%. The end of 2008 target rose from 2.3% to 4.3%.

Now what if your long-run inflation target were 4% as Paul Krugman has suggested, and then used the adjusted inflation target for NGDP targeting? The adjusted inflation target rises by 4%. For example, the end of 2008 adjusted target rose to 6.3% from 2.3%.

Let's put some numbers into the policy rule for NGDP targeting assuming a short term real rate of 0% and a current core inflation of 1.7%. Let's average core inflation back to the end of 2008. What Fed rate would the policy rule prescribe for us?

So if you want a LR inflation target at or above 3.5% for your NGDP targeting, you would keep the Fed rate at its zero lower bound because the policy rule is giving a Fed rate below 0%. However, if you wanted a LR inflation target below 3.5% for your NGDP targeting, you would want the Fed rate above the ZLB. (assuming a short term real rate of 0%).

So NGDP targeting could be a good idea for balancing inflation to its LR target over time, but the method seems open to a lot of discretion. How far back do we average core inflation? What should the LR inflation target be? And in that range of discretion, the policy rule would give a wide range of options. Is it any wonder that discretionary monetary policy is dominant now?

01/12/2015

In the determination of Effective Demand, both headline inflation and core inflation are used. How does each one affect effective demand?

Headline inflation...

If headline inflation rises (holding all else constant), effective demand will fall. However, there is a force to slow the fall of effective demand. As headline inflation rises, the effective demand monetary rule will want to prescribe a higher rate for the Fed rate. However, if the Fed rate does not change, then the Fed rate separates farther lower from the ED rule rate. This indirectly creates a looser monetary policy which raises effective demand.

So which dominates effective demand, headline inflation or the now looser monetary policy? The answer according to the equations I now use for effective demand say that headline inflation dominates. For example, if headline inflation rises by 10% from 0% to 10% over a one year period, then core inflation would have to rise by 6.8%, from 0% to 6.8% in order for effective demand to not change.

Core inflation...

So if a rise in core inflation will neutralize part of the rise in headline inflation, it is apparent that a rise in core inflation raises effective demand (as long as the Fed rate does not change).

Currently we see headline inflation dropping. Core inflation may rise as low oil prices allow consumers to spend more on core items. Assuming that the Fed rate will stay constant at the ZLB, then a fall in headline inflation will increase effective demand. Moreover, an increase in core inflation will also increase effective demand.

How can the difference be explained? Headline inflation affects overall purchases more directly. Core inflation reflects changes in monetary policy since core inflation is the basis of policy setting. So headline inflation is a factor for how inflation affects overall demand. Core inflation is a factor for determining the looseness or tightness of monetary policy. So both headline and core inflation affect effective demand in opposite yet complementary ways.

We can also see why central banks should not over-react to headline inflation. If headline inflation rises, a higher CB rate would decrease effective demand even further. The key is to allow core inflation to rise along with headline inflation making monetary policy indirectly looser. If core inflation was to rise more than 68% of the rise in headline inflation, then the central bank could worry about inflation enough to consider tightening policy against inflation.

01/08/2015

We are seeing a resurgence of effective demand from both long term yields (borrowing costs) and headline inflation falling.

What if 10-year yields fall to 1.6% by 2nd quarter 2015? And what if headline inflation falls to -0.5% by 2nd Q too? (Barclays is predicting negative headline inflation through 2015, Matthew B tweet.) I graph what effective demand would look like keeping other factors constant (labor share, net exports, government expenditures, private investment, Fed rate at ZLB).

This resurgence in effective demand would make the US economy grow faster. Unemployment would come down more. Capacity utilization would go up more. We most likely would see a boost in real wages.

Core inflation can withstand the effects of lower oil prices that give some pricing power to other products and services. This helps the Fed in their desire to raise the Fed rate later this year. Still any setback to effective demand from a rise in the Fed rate looks to be already completely neutralized and more.

Are there dangers in inflating effective demand so much, so quickly? Eventually headline inflation will rise back to normal. Eventually the longer term 10-year rate stabilizes. Put these together at some point in the future, and you reverse the resurgence. Effective demand will normalize back down.

If the utilization of labor and capital grow too much beyond a normalized effective demand level during the temporary resurgence, then I would expect the economy to contract when effective demand normalizes back down. However this temporary resurgence may be the boost that many economists have been hoping for to get the economy back to full-employment.